Regression Models for Categorical Dependent Variables Using Stata, Third Edition, Long, J. Scott
Старое издание
Автор: Rabe-hesketh, Sophia (university Of California, Berkeley, Usa) Skrondal, Anders (london School Of Economics, Uk) Название: Multilevel and longitudinal modeling using stata, volume ii ISBN: 1597181382 ISBN-13(EAN): 9781597181389 Издательство: Taylor&Francis Рейтинг: Цена: 71450.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Is it really possible to enjoy the Old Testament? Eric Seibert understands why many Christians find this part of the Bible confusing, theologically troubling, or just uninteresting. Offering dozens of practical exercises for hands-on interaction with the text, this unique resource equips readers with a variety of creative approaches to bring even the seemingly dry passages to life.
Автор: Wicher Bergsma; Marcel A. Croon; Jacques A. Hagena Название: Marginal Models ISBN: 1441918736 ISBN-13(EAN): 9781441918734 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Marginal models are often the best way of answering research questions involving dependent observations. This comprehensive overview of the basic principles of marginal modeling offers a wide range of possible applications through many real world examples.
Автор: Melamed, David Название: Applications of Regression for Categorical Outcomes Using R ISBN: 0367894637 ISBN-13(EAN): 9780367894634 Издательство: Taylor&Francis Рейтинг: Цена: 158230.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Melamed, David Название: Applications of Regression for Categorical Outcomes Using R ISBN: 1032509511 ISBN-13(EAN): 9781032509518 Издательство: Taylor&Francis Рейтинг: Цена: 63280.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Stokes Maura E., Davis Charles S., Koch Gary G. Название: Categorical Data Analysis Using SAS, Third Edition ISBN: 1607646641 ISBN-13(EAN): 9781607646648 Издательство: Неизвестно Рейтинг: Цена: 159330.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Kunihiro Suzuki Название: Statistics. Volume 3: Categorical and Time Dependent Data Analysis ISBN: 1536151246 ISBN-13(EAN): 9781536151244 Издательство: Nova Science Рейтинг: Цена: 252370.00 T Наличие на складе: Невозможна поставка. Описание: We utilize statistics when we evaluate TV program ratings, predict voting outcomes, prepare stock, predict the amount of sales, and evaluate the effectiveness of medical treatment. We want to predict the results not on the basis of personal experience or images, but on the basis of corresponding data. The accuracy of the prediction depends on the data and related theories. It is easy to show input and output data associated with a model without understanding it. However, the models themselves are not perfect, because they contain assumptions and approximations in general. Therefore, the application of the model to the data should be careful. We should know what model we should apply to the data, what parameters are assumed in the model, and what we can state based on the results of the models.Let us consider a coin toss, for example. When we perform a coin toss, we obtain a head or a tail. If we try the toss a coin three times, we may obtain the results of two heads and one tail. Therefore, the probability that we obtain for heads is , and the one that we obtain for tails is . This is a fact and we need not to discuss this any further. It is important to notice that the probability ( ) of getting a head is limited to this trial. Therefore, we can never say that the probability that we obtain for heads with this coin is , in which we state general characteristics of the coin. If we perform the coin toss trial 400 times and obtain heads 300 times, we may be able to state that the probability of obtaining a head is as the characteristics of the coin. What we can state based on the obtained data depends on the sample number. Statistics gives us a clear guideline under which we can state something is based on the data with corresponding error ranges.Mathematics used in statistics is not so easy. It may be tough work to acquire the related techniques. Fortunately, software development makes it easy to obtain results. Therefore, many members who are not specialists in mathematics can perform statistical analysis with these types of software. However, it is important to understand the meaning of the model, that is, why some certain variables are introduced and what they express, and what we can state based on the results. Therefore, understanding mathematics related to the models is invoked to appreciate the results.In this book, the authors treat models from fundamental ones to advanced ones without skipping their derivation processes. It is then possible to clearly understand the assumptions and approximations used in the models, and hence understand the limitation of the models.The authors also cover almost all the subjects in statistics since they are all related to each other, and the mathematical treatments used in a model are frequently used in the other ones.Additionally, many good practical and theoretical books on statistics are presented [1]-[10]. However, these books are oriented to special cases: Fundamental, mathematical, or special subjects. The author also aims to connect theories to practical subjects. He hopes that this book will aid readers in furthering their knowledge of special cases in statistics.
Автор: Xu, Jun Название: Modern applied regressions ISBN: 0367173875 ISBN-13(EAN): 9780367173876 Издательство: Taylor&Francis Рейтинг: Цена: 91860.00 T Наличие на складе: Нет в наличии. Описание: Modern Applied Regressions creates an intricate mural with mosaics of categorical and limited response variable (CLRV) models using both Bayesian and Frequentist approaches. Written for graduate students, junior researchers, and quantitative analysts in behavioral, health, and social sciences.
Автор: Roverato Alberto Название: Graphical Models for Categorical Data ISBN: 1108404960 ISBN-13(EAN): 9781108404969 Издательство: Cambridge Academ Рейтинг: Цена: 31670.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: For advanced students of network data science, this compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature. It focuses on the discrete case where all variables involved are categorical and, in this context, it achieves a unified presentation of classical and recent results.
Автор: Heck, Ronald H Название: Multilevel Modeling of Categorical Outcomes Using IBM SPSS ISBN: 1848729561 ISBN-13(EAN): 9781848729568 Издательство: Taylor&Francis Рейтинг: Цена: 51030.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Ronald H Heck, Scott Thomas, Lynn Tabata Название: Multilevel Modeling of Categorical Outcomes Using IBM SPSS ISBN: 1848729553 ISBN-13(EAN): 9781848729551 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Невозможна поставка. Описание: This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors’ highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.
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